Tail Event Driven ASset allocation: evidence from equity and mutual funds’ markets

Wolfgang Härdle, David Kuo Chuen Lee (), Sergey Nasekin () and Alla Petukhina
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David Kuo Chuen Lee: Singapore University of Social Sciences (SUSS)
Sergey Nasekin: Lancaster University

Journal of Asset Management, 2018, vol. 19, issue 1, No 6, 49-63

Abstract: Abstract The correlation structure across assets and opposite tail movements are essential to the asset allocation problem, since they determine the level of risk in a position. Correlation alone is not informative on the distributional details of the assets. Recently introduced TEDAS—Tail Event Driven ASset allocation approach determines the dependence between assets at different tail measures. TEDAS uses adaptive Lasso-based quantile regression in order to determine an active set of negative coefficients. Based on these active risk factors, an adjustment for intertemporal correlation is made. In this research, authors aim to develop TEDAS, by introducing three TEDAS modifications differing in allocation weights’ determination: a Cornish–Fisher Value-at-Risk minimization, Markowitz diversification rule or naïve equal weighting. TEDAS strategies significantly outperform other widely used allocation approaches on two asset markets: German equity and Global mutual funds.

Keywords: Adaptive lasso; Portfolio optimization; Quantile regression; Value-at-Risk; Tail events (search for similar items in EconPapers)
JEL-codes: C00 C14 C50 C58 (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (3)

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Working Paper: Tail event driven ASset allocation: Evidence from equity and mutual funds' markets (2015)
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DOI: 10.1057/s41260-017-0060-9

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